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    On the performance of key pre-distribution for RPL-based IoT Networks

    El hajjar, Ayman and Roussos, George and Paterson, Maura B. (2016) On the performance of key pre-distribution for RPL-based IoT Networks. In: Mitton, N. and Chaouchi, H. and Noel, T. and Watteyne, T. and Gabillon, A. and Capolsini, P. (eds.) Interoperability, Safety and Security in IoT. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 190. Springer. ISBN 9783319527260.

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    Abstract

    A core ingredient of the the Internet of Things (IoT) is the use of deeply embedded resource constrained devices, often connected to the Internet over Low Power and Lossy Networks. These constraints compounded by the need for unsupervised operation within an untrusted environment create considerable challenges for the secure operation of these systems. In this paper, we propose a novel method to secure an edge IoT network using the concept of key pre-distribution proposed by Eschenauer and Gligor in the context of distributed sensor networks. First, we investigate the performance of the unmodified algorithm in the Internet of Things setting and then analyse the results with a view to determine its performance and thus its suitability in this context. Specifically, we investigate how ring size influences performance in order to determine the required ring size that guarantees full connectivity of the network. We then proceed to propose a novel RPL objective function and associated metrics that ensure that any node that joins the network can establish secure communication with Internet destinations. , N., , H., , Th., , Th., , A., , P.

    Metadata

    Item Type: Book Section
    Additional Information: Second International Conference, InterIoT 2016 and Third International Conference, SaSeIoT 2016, Paris, France, October 26-27, 2016, Revised Selected Papers. Series ISSN: 1867-8211
    Keyword(s) / Subject(s): Internet of Things, key pre-distribution, RPL
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab, Innovation Management Research, Birkbeck Centre for
    Depositing User: Ayman El hajjar
    Date Deposited: 16 Nov 2016 14:15
    Last Modified: 09 Aug 2023 12:39
    URI: https://eprints.bbk.ac.uk/id/eprint/16737

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